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README.md

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----
-annotations_creators:
-- found
-language_creators:
-- found
-language:
-- da
-- en
-- lv
-- nb
-- zh
-license:
-- c-uda
-multilinguality:
-- multilingual
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- translation
-task_ids: []
-pretty_name: CodeXGlueTtTextToText
-tags:
-- code-documentation-translation
-dataset_info:
-- config_name: da_en
-  features:
-  - name: id
-    dtype: int32
-  - name: source
-    dtype: string
-  - name: target
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 8163215
-    num_examples: 42701
-  - name: validation
-    num_bytes: 190340
-    num_examples: 1000
-  - name: test
-    num_bytes: 190780
-    num_examples: 1000
-  download_size: 8007867
-  dataset_size: 8544335
-- config_name: lv_en
-  features:
-  - name: id
-    dtype: int32
-  - name: source
-    dtype: string
-  - name: target
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 3644127
-    num_examples: 18749
-  - name: validation
-    num_bytes: 192519
-    num_examples: 1000
-  - name: test
-    num_bytes: 190875
-    num_examples: 1000
-  download_size: 3778501
-  dataset_size: 4027521
-- config_name: no_en
-  features:
-  - name: id
-    dtype: int32
-  - name: source
-    dtype: string
-  - name: target
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 8761795
-    num_examples: 44322
-  - name: validation
-    num_bytes: 203823
-    num_examples: 1000
-  - name: test
-    num_bytes: 197135
-    num_examples: 1000
-  download_size: 8606833
-  dataset_size: 9162753
-- config_name: zh_en
-  features:
-  - name: id
-    dtype: int32
-  - name: source
-    dtype: string
-  - name: target
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 9592196
-    num_examples: 50154
-  - name: validation
-    num_bytes: 192155
-    num_examples: 1000
-  - name: test
-    num_bytes: 195245
-    num_examples: 1000
-  download_size: 9353684
-  dataset_size: 9979596
----
-# Dataset Card for "code_x_glue_tt_text_to_text"
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits-sample-size)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text
-
-### Dataset Summary
-
-CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text
-
-The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/.
-
-### Supported Tasks and Leaderboards
-
-- `machine-translation`: The dataset can be used to train a model for translating Technical documentation between languages.
-
-### Languages
-
-da_en, lv_en, no_en, zh_en
-
-## Dataset Structure
-
-### Data Instances
-
-#### da_en
-
-An example of 'test' looks as follows.
-```
-{
-    "id": 0, 
-    "source": "4 . K\u00f8r modellen , og udgiv den som en webtjeneste .\n", 
-    "target": "4 . Run the model , and publish it as a web service .\n"
-}
-```
-
-#### lv_en
-
-An example of 'train' looks as follows.
-```
-{
-    "id": 0, 
-    "source": "title : Pakalpojumu objektu izveide\n", 
-    "target": "title : Create service objects\n"
-}
-```
-
-#### no_en
-
-An example of 'validation' looks as follows.
-```
-{
-    "id": 0, 
-    "source": "2 . \u00c5pne servicevaren du vil definere komponenter fra en stykkliste for .\n", 
-    "target": "2 . Open the service item for which you want to set up components from a BOM .\n"
-}
-```
-
-#### zh_en
-
-An example of 'validation' looks as follows.
-```
-{
-    "id": 0, 
-    "source": "& # 124 ; MCDUserNotificationReadStateFilterAny & # 124 ; 0 & # 124 ; \u5305\u62ec \u901a\u77e5 , \u800c \u4e0d \u8003\u8651 \u8bfb\u53d6 \u72b6\u6001 \u3002 & # 124 ;\n", 
-    "target": "&#124; MCDUserNotificationReadStateFilterAny &#124; 0 &#124; Include notifications regardless of read state . &#124;\n"
-}
-```
-
-### Data Fields
-
-In the following each data field in go is explained for each config. The data fields are the same among all splits.
-
-#### da_en, lv_en, no_en, zh_en
-
-|field name| type |              description               |
-|----------|------|----------------------------------------|
-|id        |int32 | The index of the sample                |
-|source    |string| The source language version of the text|
-|target    |string| The target language version of the text|
-
-### Data Splits
-
-|name |train|validation|test|
-|-----|----:|---------:|---:|
-|da_en|42701|      1000|1000|
-|lv_en|18749|      1000|1000|
-|no_en|44322|      1000|1000|
-|zh_en|50154|      1000|1000|
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-https://github.com/microsoft, https://github.com/madlag
-
-### Licensing Information
-
-Computational Use of Data Agreement (C-UDA) License.
-
-### Citation Information
-
-```
-@article{CodeXGLUE,
-         title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
-         year={2020},}
-```
-
-### Contributions
-
-Thanks to @madlag (and partly also @ncoop57) for adding this dataset.

code_x_glue_tt_text_to_text.py

@@ -1,106 +0,0 @@
-from typing import List
-
-import datasets
-
-from .common import Child
-from .generated_definitions import DEFINITIONS
-
-
-_DESCRIPTION = """The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/."""
-_CITATION = """@article{DBLP:journals/corr/abs-2102-04664,
-  author    = {Shuai Lu and
-               Daya Guo and
-               Shuo Ren and
-               Junjie Huang and
-               Alexey Svyatkovskiy and
-               Ambrosio Blanco and
-               Colin B. Clement and
-               Dawn Drain and
-               Daxin Jiang and
-               Duyu Tang and
-               Ge Li and
-               Lidong Zhou and
-               Linjun Shou and
-               Long Zhou and
-               Michele Tufano and
-               Ming Gong and
-               Ming Zhou and
-               Nan Duan and
-               Neel Sundaresan and
-               Shao Kun Deng and
-               Shengyu Fu and
-               Shujie Liu},
-  title     = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
-               and Generation},
-  journal   = {CoRR},
-  volume    = {abs/2102.04664},
-  year      = {2021}
-}"""
-
-
-class CodeXGlueTtTextToTextImpl(Child):
-    _DESCRIPTION = _DESCRIPTION
-    _CITATION = _CITATION
-
-    _FEATURES = {
-        "id": datasets.Value("int32"),  # The index of the sample
-        "source": datasets.Value("string"),  # The source language version of the text
-        "target": datasets.Value("string"),  # The target language version of the text
-    }
-
-    _SUPERVISED_KEYS = ["target"]
-
-    KEYS = ["source", "target"]
-
-    SPLITS = {"train": datasets.Split.TRAIN, "dev": datasets.Split.VALIDATION, "test": datasets.Split.TEST}
-
-    def generate_urls(self, split_name):
-        lang_pair = self.info["parameters"]["natural_language_pair"]
-        for i, lang in enumerate(lang_pair.split("-")):
-            yield self.KEYS[i], f"{split_name}/{lang_pair}.{split_name}.{lang}"
-
-    def _generate_examples(self, split_name, file_paths):
-        # Open each file (one for source language and the other for target language)
-        files = {k: open(file_paths[k], encoding="utf-8") for k in file_paths}
-
-        id_ = 0
-        while True:
-            # Read a single line from each file
-            entries = {k: files[k].readline() for k in file_paths}
-
-            empty = self.check_empty(entries)
-            if empty:
-                # We are done: end of files
-                return
-
-            entries["id"] = id_
-            yield id_, entries
-            id_ += 1
-
-
-CLASS_MAPPING = {
-    "CodeXGlueTtTextToText": CodeXGlueTtTextToTextImpl,
-}
-
-
-class CodeXGlueTtTextToText(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIG_CLASS = datasets.BuilderConfig
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=name, description=info["description"]) for name, info in DEFINITIONS.items()
-    ]
-
-    def _info(self):
-        name = self.config.name
-        info = DEFINITIONS[name]
-        if info["class_name"] in CLASS_MAPPING:
-            self.child = CLASS_MAPPING[info["class_name"]](info)
-        else:
-            raise RuntimeError(f"Unknown python class for dataset configuration {name}")
-        ret = self.child._info()
-        return ret
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        return self.child._split_generators(dl_manager=dl_manager)
-
-    def _generate_examples(self, split_name, file_paths):
-        return self.child._generate_examples(split_name, file_paths)

common.py

@@ -1,75 +0,0 @@
-from typing import List
-
-import datasets
-
-
-# Citation, taken from https://github.com/microsoft/CodeXGLUE
-_DEFAULT_CITATION = """@article{CodeXGLUE,
-         title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
-         year={2020},}"""
-
-
-class Child:
-    _DESCRIPTION = None
-    _FEATURES = None
-    _CITATION = None
-    SPLITS = {"train": datasets.Split.TRAIN}
-    _SUPERVISED_KEYS = None
-
-    def __init__(self, info):
-        self.info = info
-
-    def homepage(self):
-        return self.info["project_url"]
-
-    def _info(self):
-        # This is the description that will appear on the datasets page.
-        return datasets.DatasetInfo(
-            description=self.info["description"] + "\n\n" + self._DESCRIPTION,
-            features=datasets.Features(self._FEATURES),
-            homepage=self.homepage(),
-            citation=self._CITATION or _DEFAULT_CITATION,
-            supervised_keys=self._SUPERVISED_KEYS,
-        )
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        SPLITS = self.SPLITS
-        _URL = self.info["raw_url"]
-        urls_to_download = {}
-        for split in SPLITS:
-            if split not in urls_to_download:
-                urls_to_download[split] = {}
-
-            for key, url in self.generate_urls(split):
-                if not url.startswith("http"):
-                    url = _URL + "/" + url
-                urls_to_download[split][key] = url
-
-        downloaded_files = {}
-        for k, v in urls_to_download.items():
-            downloaded_files[k] = dl_manager.download_and_extract(v)
-
-        return [
-            datasets.SplitGenerator(
-                name=SPLITS[k],
-                gen_kwargs={"split_name": k, "file_paths": downloaded_files[k]},
-            )
-            for k in SPLITS
-        ]
-
-    def check_empty(self, entries):
-        all_empty = all([v == "" for v in entries.values()])
-        all_non_empty = all([v != "" for v in entries.values()])
-
-        if not all_non_empty and not all_empty:
-            raise RuntimeError("Parallel data files should have the same number of lines.")
-
-        return all_empty
-
-
-class TrainValidTestChild(Child):
-    SPLITS = {
-        "train": datasets.Split.TRAIN,
-        "valid": datasets.Split.VALIDATION,
-        "test": datasets.Split.TEST,
-    }

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dataset_infos.json

@@ -1 +0,0 @@
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